GPvam: Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling

An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, is used to estimate the generalized, variable, and complete persistence models, Mariano et al. (2010) <doi:10.3102/1076998609346967>. These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects.

Version:	3.0-8
Depends:	R (≥ 3.2.0), Matrix
Imports:	numDeriv, Rcpp (≥ 0.11.2), graphics, grDevices, methods, stats, utils
LinkingTo:	Rcpp, RcppArmadillo
Published:	2022-09-03
Author:	Andrew Karl, Yan Yang, and Sharon Lohr
Maintainer:	Andrew Karl <akarl at asu.edu>
License:	GPL-2
NeedsCompilation:	yes
Materials:	NEWS
CRAN checks:	GPvam results

Documentation:

Reference manual:

GPvam.pdf

Downloads:

Package source:	GPvam_3.0-8.tar.gz
Windows binaries:	r-devel: GPvam_3.0-8.zip, r-release: GPvam_3.0-8.zip, r-oldrel: GPvam_3.0-8.zip
macOS binaries:	r-release (arm64): GPvam_3.0-7.tgz, r-oldrel (arm64): GPvam_3.0-7.tgz, r-release (x86_64): GPvam_3.0-8.tgz, r-oldrel (x86_64): GPvam_3.0-8.tgz
Old sources:	GPvam archive

Linking:

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